The exemplary embodiment relates to image processing. It finds particular application in connection with the mapping of images from a higher to a lower dynamic range.
The “dynamic range” of a scene, image, or a reproduction device is defined as the ratio between the highest and lowest luminance levels. Recent technologies have made it relatively easy to create radiance maps for High Dynamic Range (HDR) sceneries. Conventional low dynamic range (LDR) reproduction devices, such as printers and CRT monitors, are typically 8-bit, i.e., the luminance can range in integer values from 0 to 255. These devices are not able to directly reproduce high dynamic range images (usually 12, 16, or even 32 bits per channel). However, realistic reproduction of high contrast scenery on conventional reproduction devices is required in the printing industry, photographing industry, and for computer graphics.
If the same quantization step is used to convert from high to low dynamic range, then either the brightest part of the image or the darkest part of the image is often lost. Several tone reproduction techniques for dynamic range compression have been proposed. However, most of these techniques are unable to reproduce the local contrast and fine details of the scenery and tend to introduce artifacts. Techniques that attempt to overcome this drawback are frequently computationally expensive. In addition, these methods generally include image-dependent manual parameter adjustments, which makes them hard to be utilized in an automated display or printing process.
Incorporation by Reference
The following references, the disclosures of which are incorporated herein in their entireties by reference, are mentioned:
U.S. Pat. No. 5,450,502 by Eschbach, et al. discloses a method of improving the global contrast in a natural scene image, in which the image is converted from an original set of color coordinates to an expression where one term has a relationship to overall image intensity. A global histogram of the image is derived for that term, which plots the populations of pixels at each possible level of intensity in the image. The signal describing the histogram is operated on with a filter that weakens strong peaks and valleys in the function, without affecting flat portions of the signal. The filtered histogram signal is used for controlling the TRC mapping in a device at which the image is to be printed. The image is divided into a number of segments, each describable by a local histogram signal for that image segment. Each local histogram signal is compared to the global histogram, to determine which signals are flatter. If any of the local histograms have signals flatter than the global histogram, the signals are summed into a relevant histogram signal and directed to the flattening filter in its place.
U.S. Pat. No. 5,581,370 by Fuss, et al. discloses a method of improving the global contrast in a natural scene image. A relevant histogram of the image is derived from a selected subset of local histograms representing regions of the image. The signal describing the histogram is operated on with a filter that weakens strong peaks and valleys in the function, without affecting flat portions of the signal. The filtered histogram signal is used for controlling the TRC mapping in a device on which the image is to be printed.
U.S. Pat. No. 6,826,310 to Trifonov, et al., discloses a global method of automatic contrast correction which includes representing digital image data in the form of a brightness histogram, determining a measure of central tendency for the histogram, adding a shift value to the measure, and estimating a gamma-value from the desired shift. Both the determined and adjusted measures of central tendency are used to determine the exponent of a tone reproduction curve.
U.S. Pat. No. 6,850,642 by Wang discloses a dynamic range equalization method which includes obtaining a signal indicative of an image and forming an original histogram indicative of the signal, including information indicative of numbers of dynamic range levels in the signal. A mapping function relates each dynamic range level to positions of peaks in the original histogram. The original histogram is scaled based on the mapping function. Widths of peak areas in the original histogram are determined and the dynamic range levels are weighted based on the widths of the peak areas.